An Adaptive IoT-Based Framework for Crime Surveillance and Prevention

Crime monitoring & crime prevention has become a prominent issue in modern urban city a large & so an intelligent surveillance system is necessary is being created. This paper presents an IoT-based crime monitoring framework with integrated various sensor types involving flame, vibration, motion detection and sound sensors for improvement of security measures. The main target is to implement a real-time system that can early detect possible danger and suspicious activity to assist law enforcement agencies to intervene in time. The novelty of this work is in using a combination of multiple sensor inputs with user-friendly web interfaced for straightforward monitoring and quick decision making. The proposed framework uses ESP32 based microcontrollers for the compilation of and processing the real-time sensor data, that is displayed as interactive portal. The system’s efficiency was tested with multiple test scenarios and proving its ability to identify anomalies with a high degree of accuracy. Results point to multi-sensor information system increase of crime detection reliability and the cut of false alarms and situational awareness. The study reveals that the system proposed is a viable solution for real time crime surveillance application. It is a cost effective and scalable solution for smart security applications in the urban area, residential places and commercial places and thus helps in providing the better public safety and preventing the crime.